Developments in speech recognition technologies support more natural language interaction between services, systems and customers than previously supported. One of the most promising applications of speech recognition technology, Automatic Call Routing (ACR), seeks to determine why a customer has called a service center and to route the customer to an appropriate service agent for customer request servicing. Speech recognition technology generally allows an ACR application to recognize natural language statements from the customer, thus minimizing reliance on conventional menu systems. This permits a customer to state the purpose of their call “in their own words”.
In order for an ACR application to properly route calls, the ACR generally must interpret the intent of the customer, identify the type or category of customer call, and identify the correct routing destination for the call type. An ACR application may attempt to match one or words in a statement by a customer to a particular pre-defined action to be taken by the ACR application.
Although speech recognition technology has been improving over the years, speech recognition systems are limited by the quality and robustness of the statistical language models or other techniques used to recognize speech. Given these limits, developers of these systems strive to develop prompts, announcements, and other instructions to the users of such systems that guide these users to provide speech input that conforms with the capabilities of the particular speech recognition technology used by the system. Subtle differences in the way prompts or other instructions are worded may result in substantial differences in system performance.